Our mission is to be the catalyst for massive, measurable, data-informed healthcare improvement through:
Data: integrate data in a flexible, open & scalable platform to power healthcare’s digital transformation
Analytics: deliver analytic applications & services that generate insight on how to measurably improve
Expertise: provide clinical, financial & operational experts who enable & accelerate improvement
Engagement: attract, develop and retain world-class team members by being a best place to work
In line with its mission to achieve massive, sustained healthcare outcome improvements, Health Catalyst recently launched a new Life Science Business Unit based in Cambridge, MA, that will develop solutions to support the rapidly changing world of research, development and commercialization in the life sciences industry including, but not limited to drug development, medical devices, digital therapeutics, and risk-based contracting. Health Catalyst aims to stand out in this rapidly expanding market by focusing on solutions for the life sciences industry that ensure improved health outcomes both at the provider and patient level. The new Business Unit will support the life science industry and regulators to improve probability of R&D pipeline success, optimize clinical trial design and enrollment, and perform post-launch RWD retrospective studies. Health Catalyst aims to become a leading provider of real-world insights that will allow the industry to ground their decisions in real-time, ethical access to massive, high quality data across all therapeutic indications to tackle unmet medical needs and further improve outcomes for patients. Crucially, by leveraging the deep relationship built over time with 400+ hospitals reaching out to 100M+ patients Health Catalyst can go beyond data aggregation and data crunching, developing engaging provider and patient-facing solutions with the Life Sciences industry, to obtain deeper, richer insights.
The Data Engineer for the Life Sciences Business will be responsible for going into client environments to augment existing professional services resources in building out client data, including the acquisition of source marts and harmonized data marts (DOS Marts). The Data Engineer will help the Life Sciences business achieve the goal of having a homogenous set of data elements across clients that will enable cross-client data analytics. Additionally, the Data Engineer will assist clients in extending the standard set of data available across each client, for instance integrating clinical text data and data from patient registries.
This role is a great fit for someone who has significant data management and acquisition experience in the healthcare space. The work that the Data Engineer performs will have immediate impact on healthcare providers, but also contribute to the mission of accelerating clinical innovation and precision medicine through novel Life Sciences partnerships.
Duties & Responsibilities
Work with Life Sciences colleagues to understand data engineering priorities, including what are standard data elements that should be available at all clients, and novel data elements that would be of value towards enabling machine learning, precision oncology, pragmatic clinical trials, and more.
Collaborate with Technical Directors and Data Engineers deployed to each provider site to align on priorities and approach for contributing to data acquisition process.
Communicate project plan to client teams, including discussing the benefits of a homogenous and extended set of data elements, and bringing in colleagues across Life Sciences and other DOS Mart product leads as appropriate to communicate value proposition.
Identify sources from which requisite data live, and ETL into client DOS (Data Operating System) Source Marts.
Transform data from Source Marts into harmonized data models including Health Catalyst’s trademark DOS Marts for common standardized data, and Subject Area Marts that serve domain-specific needs.
Work closely with Life Sciences to track and update colleagues on progress of building out data marts within client environments and ensure the availability of data for Life Sciences analytics purposes.
Applied technical experience with: SQL, ETL development, database structures, data modeling, hosted solutions.
Excellent troubleshooting and problem-solving skills with being able to dig deeper to identify SQL Server/Azure performance issues and root cause the issue.
Must have strong understanding of data warehousing and analytic principles and possess the ability to explain general data warehousing concepts to technical and non-technical people.
Strong project management capabilities, with the ability to engage with and follow-up with healthcare clients and solicit information and feedback as required.
Exposure to data management technologies including SQL Databases, data warehouses, data lakes, NoSQL, Hadoop
Experience building solutions for handling unstructured data such as notes, imaging data, and raw genomic data such as BAM files
Strong experience with Extract, Transform, and Load (ETL) processes and concepts. Familiarity with multiple ETL applications is a bonus.
Strong computational skills via SQL, Python, etc.
Experience working with cloud technologies (AWS, Azure, Google) strongly preferred
Knowledge of healthcare-related ontologies/terminologies (ICD, LOINC, RxNorm, etc.) a plus
Must have excellent verbal and written communication
Education & Relevant Experience
BS in Computer Science, Health Informatics, or related field
2+ years of experience working in a SQL-based data engineering role
2+ years of experience with clinical/healthcare data
Experience in programming/scripting languages such as Python a plus